Cheaper Computing Enables Software to Program the World

Fund V’s thesis is a continuation of Fund I’s thesis, famously documented by the Wall Street Journal article “Marc Andreessen on Why Software Is Eating the
World”. a16z started 7 years ago to invest in the simultaneous growth of mobile, social and cloud. Fund V focuses on 3 new trends that kickstart new businesses going forward:

Cheaper hardware: instead of twice the performance every other
year, we can have the same
performance for half the cost. Existing technology can be applied to new trends, e.g., Nvidia becoming overnight leader in AI chips with its GPUs.

All chips will be on the internet.

Software can apply to the physical world. Entrepreneurs can now write software that applies to all cars, all money, everything that flies, etc.

VCs need to evaluate new business plans and new markets they wouldn’t have
considered 7 years ago.

There will be new distributed platforms, such as Apache Spark, cryptocurrency
and AI. They may be offered by new entrants or by established cloud players,
such as AWS.

Even though we’ve been talking about IoT for years, it’s interesting to hear
a16z is doubling down on the software side of IoT. As a consumer, the physical
world certainly doesn’t feel very connected now. I can’t swallow the cost to
replace every light bulb at home with a $50 Philips
Hue. And do we really need refrigerators to talk to
the internet? Current products
seem more like experiments, similar to how companies experimented for 15 years
before the iPhone showed up and smartphones took off. I think it’ll take another
decade for the world to truly feel connected.

AI Will Be More Accessible and Will Apply to Everything

There are 3 advantages to large companies, such as Google and Facebook,
implementing AI. These factors are democratizing, and smaller players will be
able to play.

Engineering resources: AI framework software is becoming open source (e.g.,
TensorFlow), i.e., free for anyone to build
algorithms on top of. AI software and algorithms are also on the verge of going
to the cloud. All major cloud providers will provide AI-as-a-service. This frees
engineering resources to focus on the end product.

Hardware: AI is computationally intensive. Hardware is becoming cheaper,
more distributed and more accessible via the cloud. This trend is similar to how
startups no longer have to run their own servers in a closet.

Data: it takes a lot of data to train an AI algorithm. The popular belief is
it’s hard to compete with Google because no one has access to datasets as vast.
There have been a few rare cases of smaller companies assembling big datasets in
certain markets. New generation of deep learning tries to solve problems either
by using small dataset, or by using simulated data. Instead of computers
learning how to drive on the street, imagine if they can learn how to drive in a
simulated world, complete with pedestrians, natural disasters and anything else
the real world has. a16z’s portfolio company
Improbable is used as an example for simulation.
Improbable creates simulated worlds using gaming tools and train AI within
simulations in the cloud. Improbable’s SpatialOS operating system announcement
at Slush 2016 goes further to
discuss “simulations models as a service”, in which you can pay for a rain
forest model and run your own simulations. Changing the real world is expensive,
but simulation is cheap and scalable. This is the most interesting AI-related
takeaway to me. The concept makes sense at a high level. It’s hard for me to
envision exactly how much work it takes to simulate something open-ended and
complex, such as the world economy. I’m excited to see some real-life examples.

It’s becoming obvious all new business ideas will likely have an AI component,
which wasn’t the case even 12 months ago.

Entrepreneurs Need to Raise Prices

This is a smaller topic Marc Andreessen raised towards the end of the
conversation. a16z believes companies tend to be weak at go-to-market, and
charges too little. Charging higher prices means:

Being able to afford a larger salesforce and more substantial marketing
campaigns, or what Marc Andreessen calls the “too hungry to eat” problem.

As someone who have worked on multiple open source products and companies
building on top of open source technologies, this subject is often on my mind —
how do we give the product away for free and have a successful business? Is
upselling a “pro” version, selling professional services, or partnerships
sufficient to survive? a16z’s concerns match my experiences. More on this
subject in a future essay.

July•2016

I'm building products that build the next generation of companies at LTSE.
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